The present invention relates to an image forming apparatus used for printers such as laser printers, ink jet printers, thermal transfer printers, etc., and more specifically to an image forming apparatus capable of improving the quality of inputted images by reducing jaggy forms and smoothing the density variation in gray scale images.
Since a large part of image forming printers ar e designed for 300 dpi, most electronic computers output signals in accordance with 300 dpi. However, 300 dpi printers have a disadvantage of forming jaggy images. To eliminate it, the density of picture elements must be made higher. Nevertheless, high-density picture elements increase page buffers and printer costs associated with enhanced precision in an engine. Additionally, widely distributed bit map font and popular input units (scanners, etc.) for 300 dpi units cannot be used at all. With laser printers, high-density picture elements can be obtained in the vertical scanning. That is, it is very difficult to increase the pitch of form feed and drum feed. If it could, it, would cost very high. If high-density picture elements is designed in the horizontal scanning direction, the improvement can be realized more easily with a low cost. Therefore, it is proposed that the quality of images should be improved by tripling the picture element positioning precision in the horizontal direction and setting the size of a picture element in 12 variations (U.S. Pat. No. 4,847,641). With this method, inputted image picture elements are segmented by a sampling window of a predetermined form, compared with a plurality of template patterns written in a PLA (programmable logic array), and modified to the correct position and size of corresponding picture elements if they match any of the predetermined patterns.
FIG. 1 shows how to correct the position and size of picture elements. Inputted data 1 are segmented by a sampling window 2, compared with templates 3 shown to the right in FIG. 1, and corrected to the position and size of corresponding picture elements if inputted data match any of the template patterns.
FIG. 2 shows before-correction and after-correction pattern samples stored in templates 3. In FIG. 2, the patterns above each arrow shows data in a template to be corrected, and the patterns below each arrow show patterns corrected according to the data. Each of the upper patterns shows a vertical oblique line to be corrected to an appropriate vertical oblique line. For example, the left most pattern shows that the picture element at the center is moved by 1/3 element to left. In these patterns, thin black dots indicate picture elements not to be corrected in the present process.
In FIG. 2, middle patterns shows a jag reducing process on a horizontal oblique line where the size of a dot to be corrected is reduced to 60% in normal dot diameter. The two patterns in the lower right corner show a jag reducing process on a horizontal oblique line where the size of a dot to be corrected is reduced to 30% in normal dot diameter. Then, a white dot right to the corrected dot is assigned a black dot of 60% in normal dot diameter, thus reducing jags in horizontal oblique lines.
However, since the methods described by referring to FIGS. 1 and 2 require a number of template patterns, they cause problems of a low process speed, a large memory requirements for storing a large number of template patterns, and correction being performed only on picture elements at the coincident positions in template patterns.
Additional problem is that an appropriate correction cannot be performed for a pattern of, for example, a black-white-black arrangement because the correction is made only in picture element units and such arrangement cannot be made within one picture element. In addition to the jag reducing method, a there is a density variation smoothing method as another method for improving the quality of images. However, this method is not practical because a great number of picture element patterns exist in the same gray scale. Furthermore, in the method shown in FIG. 1, the quality of images is improved by correcting the position and size of a target picture element, that is, a picture element at the center of a template. Therefore, picture elements are undesirably corrected depending on the types of patterns as shown in FIG. 3, thereby resulting in worse image quality.
Besides, a picture element comes in 12 variations and the input position can be shifted for 3 positions, that is, the original, forward, and backward positions. This generates 36 selections of lighting timing, thereby causing.a large scale circuit for light modulation.